YesPlz AI

System analyzes the primary item image on the PDP.

AI identifies category (e.g., blazer) and style (e.g., formal).

Algorithm searches the database for complementary items (trousers, shoes).

A curated outfit is rendered in a carousel below the product description.

User uploads a screenshot from Instagram.

YesPlz AI extracts the silhouette and pattern vectors.

The engine matches vectors against the retailer's inventory.

Visually similar products are displayed in order of match confidence.

YesPlz tracks user's favorite styles via site interactions.

AI generates a unique outfit 'lookbook' for each subscriber.

Dynamic images are injected into the email template via API.

Personalized recommendations lead to higher engagement.

Customer scans an item tag in a physical dressing room.

The smart mirror displays 'Complete the Look' suggestions from the online catalog.

Customer requests an additional item to be brought to the room by a stylist.

Integrates brick-and-mortar with e-commerce data.

AI tags every sold item with granular attributes.

Dashboard aggregates data to show 'V-neck' products are trending higher than 'Crew-neck'.

Merchandising team adjusts future procurement based on visual data.

Inventory risk is minimized.

User interacts with an AI chat interface.

User specifies an occasion: 'Garden Party'.

AI suggests a base item and builds an entire outfit around it.

User adds the entire bundle to the cart with one click.

Raw product data is fed into the YesPlz tagger.

AI normalizes color names, sleeve lengths, and materials across the catalog.

Standardized data improves site-wide filtering and SEO.

Manual data entry errors are eliminated.